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Development and validation of a novel chronic pancreatitis pathological grade based on artificial intelligence.
Pancreatology : official journal of the International Association of Pancreatology (IAP) ... [et al.]
Apr 29, 2025
BACKGROUND: Effective chronic pancreatitis (CP) treatment requires accurate severity evaluation, but no histopathology grading system exists. This study aimed to develop and validate a novel CP pathological grade (Histopathology-derived CPpG) using q...
Intelligent predictive risk assessment and management of sarcopenia in chronic disease patients using machine learning and a web-based tool.
European journal of medical research
Apr 29, 2025
BACKGROUND: Individuals with chronic diseases are at higher risk of sarcopenia, and precise prediction is essential for its prevention. This study aims to develop a risk scoring model using longitudinal data to predict the probability of sarcopenia i...
Deep learning radiopathomics predicts targeted therapy sensitivity in EGFR-mutant lung adenocarcinoma.
Journal of translational medicine
Apr 29, 2025
BACKGROUND: Ttyrosine kinase inhibitors (TKIs) represent the standard first-line treatment for patients with epidermal growth factor receptor (EGFR)-mutant lung adenocarcinoma. However, not all patients with EGFR mutations respond to TKIs. This study...
Development and validation of machine learning models for predicting no. 253 lymph node metastasis in left-sided colorectal cancer using clinical and CT-based radiomic features.
Cancer imaging : the official publication of the International Cancer Imaging Society
Apr 29, 2025
BACKGROUND: The appropriate ligation level of the inferior mesenteric artery (IMA) in left-sided colorectal cancer (CRC) surgery is debated, with metastasis in No. 253 lymph node (No. 253 LN) being a key determining factor. This study aimed to develo...
Development and validation of machine learning models for predicting low muscle mass in patients with obesity and diabetes.
Lipids in health and disease
Apr 29, 2025
BACKGROUND AND AIMS: Low muscle mass (LMM) is a critical complication in patients with obesity and diabetes, exacerbating metabolic and cardiovascular risks. Novel obesity indices, such as the body roundness index (BRI), conicity index, and relative ...
Development and validation a radiomics combined clinical model predicts treatment response for esophageal squamous cell carcinoma patients.
BMC gastroenterology
Apr 29, 2025
PURPOSE: This study is aimed to develop and validate a machine learning model, which combined radiomics and clinical characteristics to predicting the definitive chemoradiotherapy (dCRT) treatment response in esophageal squamous cell carcinoma (ESCC)...
Application of deep learning reconstruction combined with time-resolved post-processing method to improve image quality in CTA derived from low-dose cerebral CT perfusion data.
BMC medical imaging
Apr 29, 2025
BACKGROUND: To assess the effect of the combination of deep learning reconstruction (DLR) and time-resolved maximum intensity projection (tMIP) or time-resolved average (tAve) post-processing method on image quality of CTA derived from low-dose cereb...
Automated radiography assessment of ankle joint instability using deep learning.
Scientific reports
Apr 29, 2025
This study developed and evaluated a deep learning (DL)-based system for automatically measuring talar tilt and anterior talar translation on weight-bearing ankle radiographs, which are key parameters in diagnosing ankle joint instability. The system...
Development of an artificial intelligence powered software for automated analysis of skeletal muscle ultrasonography.
Scientific reports
Apr 29, 2025
Muscle ultrasound has high utility in clinical practice and research; however, the main challenges are the training and time required for manual analysis to achieve objective quantification of muscle size and quality. We aimed to develop and validate...
Deep learning for quality assessment of axial T2-weighted prostate MRI: a tool to reduce unnecessary rescanning.
European radiology experimental
Apr 29, 2025
BACKGROUND: T2-weighted images are a critical component of prostate magnetic resonance imaging (MRI), and it would be useful to automatically assess image quality (IQ) on a patient-specific basis without radiologist oversight.
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